CN108759666A - A kind of dimension measurement method based on flight time three-dimensional camera - Google Patents
A kind of dimension measurement method based on flight time three-dimensional camera Download PDFInfo
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- CN108759666A CN108759666A CN201810524023.0A CN201810524023A CN108759666A CN 108759666 A CN108759666 A CN 108759666A CN 201810524023 A CN201810524023 A CN 201810524023A CN 108759666 A CN108759666 A CN 108759666A
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01B—MEASURING LENGTH, THICKNESS OR SIMILAR LINEAR DIMENSIONS; MEASURING ANGLES; MEASURING AREAS; MEASURING IRREGULARITIES OF SURFACES OR CONTOURS
- G01B11/00—Measuring arrangements characterised by the use of optical techniques
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01B—MEASURING LENGTH, THICKNESS OR SIMILAR LINEAR DIMENSIONS; MEASURING ANGLES; MEASURING AREAS; MEASURING IRREGULARITIES OF SURFACES OR CONTOURS
- G01B11/00—Measuring arrangements characterised by the use of optical techniques
- G01B11/02—Measuring arrangements characterised by the use of optical techniques for measuring length, width or thickness
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T19/00—Manipulating 3D models or images for computer graphics
- G06T19/20—Editing of 3D images, e.g. changing shapes or colours, aligning objects or positioning parts
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
- G06T7/60—Analysis of geometric attributes
- G06T7/62—Analysis of geometric attributes of area, perimeter, diameter or volume
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/10—Image acquisition modality
- G06T2207/10004—Still image; Photographic image
- G06T2207/10012—Stereo images
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Abstract
The present invention relates to a kind of dimension measurement methods based on flight time three-dimensional camera, light source is subjected to radio-frequency modulations, reflected light is collected by three-dimensional ToF cameras and makees related operation with demodulated signal, actively change the initial phase delay of demodulated signal, four groups of correlations are obtained, solve depth value accordingly and eliminate ambient light；For the present invention by the way that the algorithm in data conversion module and module is arranged, the camera coordinates system three-dimensional coordinate that control system is obtained to each point is converted to the length, width and height of babinet, can quick and precisely obtain the size and volume of babinet.
Description
Technical field
The present invention relates to flow volume field of measuring technique, specifically a kind of ruler based on flight time three-dimensional camera
Very little measurement method.
Background technology
The existing 3-D measuring apparatus for logistics field is the scheme based on structure light, to ambient light anti-interference ability
Difference, the infrared discrete spot especially projected in sun light direct beam can be flooded by sunlight, and Measurement Algorithm is caused to fail.
Based on this, for limitation present in above-mentioned present situation, the present invention, which proposes one kind, can solve existing size survey
By the dimension measurement method based on flight time three-dimensional camera of ambient light interference problem in amount scheme.
Invention content
In order to solve above-mentioned problems of the prior art, the present invention, which provides one kind, can solve existing dimensional measurement side
By the dimension measurement method based on flight time three-dimensional camera of ambient light interference problem in case.
The technical solution adopted by the present invention to solve the technical problems is：
A kind of dimension measurement method based on flight time three-dimensional camera, includes the following steps：
Step 1: radio-frequency modulations processing is carried out to light source by the magazine control systems of three-dimensional ToF, and by modulation treatment
Light source afterwards is emitted on babinet；
Step 2: observing reflected corresponding light by the magazine imaging systems of three-dimensional ToF, pixel seat is acquired
Each pixel point coordinates (u, v) in mark system middle case；
Step 3: by the magazine data processing modules of three-dimensional ToF, each pixel in pixel coordinate system middle case is obtained
Point coordinates (u, v) simultaneously obtains the camera coordinates system three-dimensional coordinate (X of each point by calculating conversionc, Yc, Zc)；
Step 4: control system obtains the camera coordinates system three-dimensional coordinate (X of each pointc, Yc, Zc) after be transmitted to terminal, terminal
Interior data conversion module is by the camera coordinates system three-dimensional coordinate (X of each pointc, Yc, Zc) length, width and height (L, W, H) of babinet are converted to,
And display is exported by the data outputting module in terminal.
Further, the light source after a kind of modulation treatment of the step is square wave.
Further, for conversion process specifically, setting k × l as the size of pixel, f is that imaging is in the step 3
The focal length of system, θ are the gradient of camera coordinates system, and d is measurement distance of the light source to babinet,To emit the phase of light and reflected light
Potential difference, c are light velocity constant, then the transformational relation between pixel coordinate system and camera coordinates system is,
Formula (1)：
Formula (2)：
Formula (3)：
Association type (1), formula (2), formula (3), obtain (Xc, Yc, Zc)。
Further, in the step 3, emit the phase difference of light and reflected lightSpecific calculating process be, set τ
Actively to change retardation in measuring every time,
It is measured by four times, and changes retardation τ in each measure, ambient light is constant K, is obtained：
To above-mentioned relation formula by way of differential mode, constant term K is eliminated, is obtained：
Further, in the step 4, the conversion process of the length, width and height (L, W, H) of babinet is the data conversion mould
Block is provided with judgment criterion model, using the rejecting of judgment criterion iteration and the inconsistent input data of estimated parameter, by defeated
Enter correct data estimation model parameter, specially：
S1, the initial point cloud data of the camera coordinates system three-dimensional coordinate of control system acquisition each point is randomly choosed
Point forms subset L1, and parameter A, B, C of initialization areal model, model AX+BY+CZ+D=0 are obtained with least square method；
It is the data except subset L1 that S2, the model AX+BY+CZ+D=0 obtained with step S1, which remove test subset L2, L2,
It is distance of any point to areal model that threshold value d, d, which is arranged, and the point set L ' and L1 for being less than d in subset L2 with model error constitute collection
Close L*, set L*For interior point set, remaining is point not in the know；
Point set L in S3, statistics*The number of interior point judges whether to be more than the 1/3 of the number put in initial point cloud, if so,
Then with interior point set L*Interior data estimate new model parameter A ', B ', C ', as the output of new model, if it is not, then with current
Maximum interior point set L*The number of interior point compares, if more than the number of current most imperial palace point set is then replaced, and store current mould
The parameter of type；
S4, step S1-S3 is repeated, is iterated processing, the model generated to each iteration screens, when in interior point set
Point is then given up when very little, is then replaced when more preferable than "current" model, gets rid of the point cloud of non-babinet, obtains the point of babinet
Cloud；
S5, the point cloud of babinet is filtered and is clustered, obtain the point cloud P of more accurate babinet；
S6, marginality detection is carried out to the point cloud P of acquisition, obtains the point cloud p at babinet edge；
S7, the linear edge profile of babinet is obtained to the point cloud p progress straight-line detection of acquisition；
S8, find babinet linear edge profile extreme coordinates, the length, width and height (L, W, H) of babinet are obtained by calculation；
S9, box volume is calculated by the product of length, width and height.
Further, in the step S2, threshold value d is set as 0.01m.
Further, in the step S4, iterations are set as 50 times.
Further, in the step S5,
Filtering includes straight-through filtering and Statis Outlier Removal filter filterings, and the straight-through filtering was used for
Left and right noise is filtered, the Statis Outlier Removal filters filter outliers calculate each point and arrive and this institute
There are the average distance of point of proximity, point of the average distance except a standard deviation range, as outlier；
Cluster is distance cluster, the noise to get up with other cohesions for isolating babinet.
Further, in the step S6, marginality detection process is：
For in cloud P a point q and the nearest k point of distance q be fitted, obtain in a least square meaning
Part plan, be denoted as ax+by+cz+d=0, the normal (a, b, c) in this face is the normal of the point, finds out the normal of all the points
Behind direction, the normal direction of k neighbor point is compared, takes the point that normal direction mutates as boundary point.
Further, in the step S7, detailed process is：
By sampling consistency, the point cloud of a plurality of line segment is obtained, the endpoint of line segment is respectively x coordinate minimax point, is led to
The direction vector of every line segment can be calculated by crossing the coordinate of two endpoints, by the direction vector angle of every line segment, to case
The length, width and height of body are classified.
Compared with prior art, the beneficial effects of the invention are as follows：
1, light source is carried out radio-frequency modulations by the present invention, is collected reflected light by three-dimensional ToF cameras and is made phase with demodulated signal
Operation is closed, actively changes the initial phase delay of demodulated signal, obtains four groups of correlations, solve depth value accordingly and eliminate environment
Light；
2, control system is obtained the camera of each point by the present invention by the way that the algorithm in data conversion module and module is arranged
Coordinate system three-dimensional coordinate is converted to the length, width and height of babinet, can quick and precisely obtain the size and volume of babinet.
Description of the drawings
Present invention will be further explained below with reference to the attached drawings and examples.
Fig. 1 is the schematic diagram that the present invention is implemented；
Fig. 2 is the work flow diagram of the present invention；
Fig. 3 is in one embodiment of the present of invention, for the figure for getting rid of before the point cloud of non-babinet 2；
Fig. 4 is in one embodiment of the present of invention, for the figure for getting rid of after the point cloud of non-babinet 2；
Fig. 5 is the figure obtained after Fig. 4 is filtered and is clustered；
Fig. 6 is the figure for Fig. 5 obtain after marginality detection；
Fig. 7 is the figure for Fig. 6 obtain after straight-line detection.
Specific implementation mode
In order to make the purpose , technical scheme and advantage of the present invention be clearer, with reference to the accompanying drawings and embodiments, right
The present invention is further elaborated.It should be appreciated that the specific embodiments described herein are merely illustrative of the present invention, and
It is not used in the restriction present invention.
As depicted in figs. 1 and 2, a kind of dimension measurement method based on flight time three-dimensional camera of the present invention, packet
Include following steps：
Step 1: radio-frequency modulations processing is carried out to light source 104 by the control system 103 in three-dimensional ToF cameras 1, and will
Light source 101 after modulation treatment is emitted on babinet 2；
Step 2: observing reflected corresponding light 102 by the imaging system 105 in three-dimensional ToF cameras 1, obtain
Each pixel point coordinates (u, v) on to pixel coordinate system middle case 2；
Step 3: by the data processing module 106 in three-dimensional ToF cameras 1, obtain each in pixel coordinate system middle case 2
Pixel point coordinates (u, v) simultaneously obtains the camera coordinates system three-dimensional coordinate (X of each point by calculating conversionc, Yc, Zc)；
Step 4: control system 103 obtains the camera coordinates system three-dimensional coordinate (X of each pointc, Yc, Zc) after be transmitted to terminal 3,
Data conversion module 301 in terminal 3 is by the camera coordinates system three-dimensional coordinate (X of each pointc, Yc, Zc) be converted to the length and width of babinet 2
High (L, W, H), and display is exported by the data outputting module 302 in terminal 3.
When it is implemented, the light source 101 after a kind of modulation treatment of step is square wave.
When it is implemented, conversion process is specifically, set k × l as the size of pixel, f is imaging in the step 3
The focal length of system 105, θ are the gradient of camera coordinates system, and d is measurement distance of the light source 104 to babinet 2,For transmitting light with
The phase difference of reflected light, c are light velocity constant, then the transformational relation between pixel coordinate system and camera coordinates system is,
Formula (1)：
Formula (2)：
Formula (3)：
Association type (1), formula (2), formula (3), obtain (Xc, Yc, Zc)。
When it is implemented, in the step 3, emit the phase difference of light and reflected lightSpecific calculating process be, set τ
Actively to change retardation in measuring every time,
It is measured by four times, and changes retardation τ in each measure, ambient light is constant K, is obtained：
To above-mentioned relation formula by way of differential mode, constant term K is eliminated, is obtained：
When it is implemented, in the step 4, the conversion process of the length, width and height (L, W, H) of babinet 2 is the data conversion
Module 301 is provided with judgment criterion model, using the rejecting of judgment criterion iteration and the inconsistent input data of estimated parameter, leads to
It crosses and inputs correct data estimation model parameter, specially：
S1, the initial point cloud data of the camera coordinates system three-dimensional coordinate of the acquisition each point of control system 103 is randomly choosed one
It is a little, subset L1 is formed, parameter A, B, C of initialization areal model, model AX+BY+CZ+D=are obtained with least square method
0；
It is the data except subset L1 that S2, the model AX+BY+CZ+D=0 obtained with step S1, which remove test subset L2, L2,
It is distance of any point to areal model that threshold value d, d, which is arranged, and the point set L ' and L1 for being less than d in subset L2 with model error constitute collection
Close L*, set L*For interior point set, remaining is point not in the know；
Point set L in S3, statistics*The number of interior point judges whether to be more than the 1/3 of the number put in initial point cloud, if so,
Then with interior point set L*Interior data estimate new model parameter A ', B ', C ', as the output of new model, if it is not, then with current
Maximum interior point set L*The number of interior point compares, if more than the number of current most imperial palace point set is then replaced, and store current mould
The parameter of type；
S4, step S1-S3 is repeated, is iterated processing, the model generated to each iteration screens, when in interior point set
Point is then given up when very little, is then replaced when more preferable than "current" model, gets rid of the point cloud of non-babinet 2, obtains the point of babinet 2
Cloud, as shown in Figure 3 and Figure 4, Fig. 3 are the figure before getting rid of the point cloud of non-babinet 2, and Fig. 4 is the point cloud for getting rid of non-babinet 2
Figure afterwards；
S5, the point cloud of babinet 2 is filtered and is clustered, obtain the point cloud P of more accurate babinet 2, as shown in Figure 5；
S6, marginality detection is carried out to the point cloud P of acquisition, obtains the point cloud p at 2 edge of babinet, as shown in Figure 6；
S7, the linear edge profile of babinet 2 is obtained to the point cloud p progress straight-line detection of acquisition, as shown in Figure 7；
S8, find babinet 2 linear edge profile extreme coordinates, be obtained by calculation babinet 2 length, width and height (L, W,
H)；
S9,2 volume of babinet is calculated by the product of length, width and height.
When it is implemented, in the step S2, threshold value d is set as 0.01m.
When it is implemented, in the step S4, iterations are set as 50 times, are meeting the unsuitable long feelings of iteration time
The maximum times of iteration are capable of in selection under condition.
When it is implemented, in the step S5,
Filtering includes straight-through filtering and Statis Outlier Removal filter filterings, and the straight-through filtering was used for
Left and right noise is filtered, the Statis Outlier Removal filters filter outliers calculate each point and arrive and this institute
There are the average distance of point of proximity, point of the average distance except a standard deviation range, as outlier；
Cluster is distance cluster, the noise to get up with other cohesions for isolating babinet.
When it is implemented, in the step S6, marginality detection process is：
For in cloud P a point q and the nearest k point of distance q be fitted, obtain in a least square meaning
Part plan, be denoted as ax+by+cz+d=0, the normal (a, b, c) in this face is the normal of the point, finds out the normal of all the points
Behind direction, the normal direction of k neighbor point is compared, takes the point that normal direction mutates as boundary point.
When it is implemented, in the step S7, detailed process is：
By sampling consistency, the point cloud of a plurality of line segment is obtained, the endpoint of line segment is respectively x coordinate minimax point, is led to
The direction vector of every line segment can be calculated by crossing the coordinate of two endpoints, by the direction vector angle of every line segment, to case
The length, width and height of body 2 are classified.
The basic principles, main features and advantages of the present invention have been shown and described above.The technology of the industry
Personnel are it should be appreciated that the present invention is not limited to the above embodiments, and the above embodiments and description only describe this
The principle of invention, without departing from the spirit and scope of the present invention, various changes and improvements may be made to the invention, these changes
Change and improvement all fall within the protetion scope of the claimed invention.The claimed scope of the invention by appended claims and its
Equivalent thereof.
Claims (10)
1. a kind of dimension measurement method based on flight time three-dimensional camera, which is characterized in that include the following steps：
Step 1: radio-frequency modulations processing is carried out to light source by the magazine control systems of three-dimensional ToF, and will be after modulation treatment
Light source is emitted on babinet；
Step 2: collecting reflected corresponding light by the magazine imaging systems of three-dimensional ToF, pixel coordinate system is acquired
Each pixel point coordinates (u, v) in middle case；
Step 3: by the magazine data processing modules of three-dimensional ToF, obtains each pixel point in pixel coordinate system middle case and sit
Mark (u, v) simultaneously obtains the camera coordinates system three-dimensional coordinate (X of each point by calculating conversionc, Yc, Zc)；
Step 4: control system obtains the camera coordinates system three-dimensional coordinate (X of each pointc, Yc, Zc) after be transmitted to terminal, in terminal
Data conversion module is by the camera coordinates system three-dimensional coordinate (X of each pointc, Yc, Zc) length, width and height (L, W, H) of babinet are converted to, and lead to
Cross the data outputting module output display in terminal.
2. a kind of dimension measurement method based on flight time three-dimensional camera according to claim 1, which is characterized in that institute
It is square wave to state the light source after a kind of modulation treatment of step.
3. a kind of dimension measurement method based on flight time three-dimensional camera according to claim 1, which is characterized in that institute
Conversion process in step 3 is stated specifically, setting k × l as the area of pixel, f is the focal length of imaging system, and θ is camera coordinates
The gradient of system, d are measurement distance of the light source to babinet,To emit the phase difference of light and reflected light, c is light velocity constant, then
Transformational relation between pixel coordinate system and camera coordinates system is,
Formula (1)：
Formula (2)：
Formula (3)：
Association type (1), formula (2), formula (3), obtain (Xc, Yc, Zc)。
4. a kind of dimension measurement method based on flight time three-dimensional camera according to claim 3, which is characterized in that institute
It states in step 3, emits the phase difference of light and reflected lightSpecific calculating process be set τ as every time measure in actively change
Retardation,
It is measured by four times, and changes retardation τ in each measure, ambient light is constant K, is obtained：
To above-mentioned relation formula by way of differential mode, constant term K is eliminated, is obtained：
5. a kind of dimension measurement method based on flight time three-dimensional camera according to claim 1, which is characterized in that institute
It states in step 4, the conversion process of the length, width and height (L, W, H) of babinet is that the data conversion module is provided with judgment criterion mould
Type passes through using the rejecting of judgment criterion iteration and the inconsistent input data of estimated parameter and inputs correct data estimation mould
Shape parameter, specially：
S1, the initial point cloud data of the camera coordinates system three-dimensional coordinate of control system acquisition each point is randomly choosed into some points, group
At subset L1, parameter A, B, C of initialization areal model, model AX+BY+CZ+D=0 are obtained with least square method；
It is the data except subset L1, setting that S2, the model AX+BY+CZ+D=0 obtained with step S1, which remove test subset L2, L2,
Threshold value d, d are distance of any point to areal model, and the point set L ' and L1 for being less than d in subset L2 with model error constitute set
L*, set L*For interior point set, remaining is point not in the know；
Point set L in S3, statistics*The number of interior point judges whether to be more than the 1/3 of the number put in initial point cloud, if it is, with
Interior point set L*Interior data estimate new model parameter A ', B ', C ', as the output of new model, if it is not, then with current maximum
Interior point set L*The number of interior point compares, if more than the number of current most imperial palace point set is then replaced, and store "current" model
Parameter；
S4, step S1-S3 is repeated, is iterated processing, the model of each iteration generation screened, when being put too in interior point set
Then give up when few, is then replaced when more preferable than "current" model, gets rid of the point cloud of non-babinet, obtain the point cloud of babinet；
S5, the point cloud of babinet is filtered and is clustered, obtain the point cloud P of more accurate babinet；
S6, marginality detection is carried out to the point cloud P of acquisition, obtains the point cloud p at babinet edge；
S7, the linear edge profile of babinet is obtained to the point cloud p progress straight-line detection of acquisition；
S8, find babinet linear edge profile extreme coordinates, the length, width and height (L, W, H) of babinet are obtained by calculation；
S9, box volume is calculated by the product of length, width and height.
6. a kind of dimension measurement method based on flight time three-dimensional camera according to claim 5, which is characterized in that institute
It states in step S2, threshold value d is set as 0.01m.
7. a kind of dimension measurement method based on flight time three-dimensional camera according to claim 5, which is characterized in that institute
It states in step S4, iterations are set as 50 times.
8. a kind of dimension measurement method based on flight time three-dimensional camera according to claim 5, which is characterized in that institute
It states in step S5,
Filtering includes straight-through filtering and Statis Outlier Removal filter filterings, and the straight-through filtering is for filtering a left side
Right noise, the Statis Outlier Removal filters filter outliers calculate each point to point is all faces with this
The average distance of near point, point of the average distance except a standard deviation range, as outlier；
Cluster is distance cluster, the noise to get up with other cohesions for isolating babinet.
9. a kind of dimension measurement method based on flight time three-dimensional camera according to claim 5, which is characterized in that institute
It states in step S6, marginality detection process is：
For in cloud P a point q and the nearest k point of distance q be fitted, obtain a least squares sense office
Facial planes is denoted as ax+by+cz+d=0, and the normal (a, b, c) in this face is the normal of the point, finds out the normal direction of all the points
Afterwards, the normal direction of k neighbor point is compared, takes the point that normal direction mutates as boundary point.
10. a kind of dimension measurement method based on flight time three-dimensional camera according to claim 5, which is characterized in that
In the step S7, detailed process is：
By sampling consistency, the point cloud of a plurality of line segment is obtained, the endpoint of line segment is respectively x coordinate minimax point, passes through two
The coordinate of a endpoint can calculate the direction vector of every line segment, by the direction vector angle of every line segment, to babinet
Length, width and height are classified.
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| CN112504125A (en) * | 2020-12-15 | 2021-03-16 | 广东工业大学 | Non-contact cuboid volume measurement method based on TOF |
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| CN109991584A (en) * | 2019-03-14 | 2019-07-09 | 深圳奥比中光科技有限公司 | A kind of jamproof distance measurement method and depth camera |
| CN110686600A (en) * | 2019-11-05 | 2020-01-14 | 北京深测科技有限公司 | Measuring method and system based on flight time measurement |
| CN110686600B (en) * | 2019-11-05 | 2021-08-06 | 北京深测科技有限公司 | Measuring method and system based on flight time measurement |
| CN112504125A (en) * | 2020-12-15 | 2021-03-16 | 广东工业大学 | Non-contact cuboid volume measurement method based on TOF |
| CN112504125B (en) * | 2020-12-15 | 2022-03-25 | 广东工业大学 | Non-contact cuboid volume measurement method based on TOF |
| CN113418467A (en) * | 2021-06-16 | 2021-09-21 | 厦门硅谷动能信息技术有限公司 | Method for detecting general and black luggage size based on ToF point cloud data |
| CN113671519A (en) * | 2021-10-22 | 2021-11-19 | 武汉市聚芯微电子有限责任公司 | Time-of-flight ranging method and device, time-of-flight camera and electronic equipment |
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